AI Models & Platforms

Precisely Debuts AI Studio with Ready-Made Apps, Agents, and Skills

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Precisely on October 6, 2026 announced the immediate availability of Precisely AI Studio, a curated collection of ready-made AI apps, agents, and skills for building AI solutions, with new users able to sign up for a free trial.

What AI Studio Includes

Assets in AI Studio work with AI tools including Claude, Microsoft Copilot, and ChatGPT, according to the company’s announcement. Precisely said the offering is built for data teams, engineers, and developers, helping them accelerate the creation of agents, skills, AI workflows, and AI-powered applications on data made more visible, reliable, accountable, and complete using the Precisely Platform. Its working examples show how to make data AI-ready using platform capabilities such as data quality and enrichment.

Some assets draw on platform capabilities directly, covering tasks such as geocoding addresses, launching governance workflows, and configuring data replication pipelines. Others build on data, including a property analyzer app and a real estate intelligence agent. The company said the collection will continue to expand over time and is designed so builders can begin prototyping within minutes.

In the announcement, Precisely cited McKinsey’s State of AI report, saying it found that nearly two-thirds of organizations are still experimenting or in pilot mode and unable to scale AI across the enterprise. The company also characterized many AI projects as stalling because builders lack a starting point, spending considerable time determining what is possible before building anything real.

Trial Terms and Product Mechanics

The AI Studio product page defines three asset types: apps are pre-built applications that deliver a full industry outcome, agents are task-focused and can be pointed at a user’s own records, and skills are building blocks users can download and drop into their own stack. Precisely describes the assets as organized by industry and outcome, and states that each one is ready-made, tested, and pre-connected via MCP.

The documented flow has three steps: users can browse the collection without an account, sign in to run assets against Precisely sample data and prompts to see how each asset behaves, and then download agents and skills to run in their own environment through a Precisely MCP connection. Precisely states that every asset is built on its proprietary datasets and embedded location intelligence and runs on live Precisely Platform capabilities, and says it remains neutral across clouds, models, and the customer’s data estate, with agents and skills composable on whatever model or tooling the user already has. The company says the environment works out of the box with no configuration required, connects to the models, tools, and applications an organization already uses through a Precisely-hosted MCP server, and lets workspace owners invite colleagues and manage members from the account menu.

Signing up for the free trial at precisely.ai creates a trial workspace with 30 days of full access. The trial includes credit and transaction allowances tracked inside AI Studio, and it ends early if those allowances are exhausted, at which point users can talk to Sales about converting to a production environment. Existing Precisely customers can set the trial workspace as their default within an existing Data Integrity Suite workspace without drawing against purchased usage allowances or entitlements.

AI Studio is available globally, though dataset availability and geographic coverage vary by capability, with coverage details provided within individual assets. The environment runs on sample data by default; two apps, Data Graph Enrich and Data Quality Boost, optionally let users upload their own data. Precisely says it is responsible for security during the trial and that uploaded data is removed when the trial ends, and it recommends against uploading sensitive or production data. For organizations weighing production use, the company advises evaluating permissions, integrations, governance requirements, and potential business impact before connecting assets to production systems, and beginning with test or non-production data. Upgrading runs through the Plan section of the account menu, where an Upgrade button opens a form for contacting Sales, and support is available through Precisely’s Help Center documentation and the AI Studio Community Forum.

Executive and Partner Statements

“Building a compelling AI demo is one thing. Building AI you can trust at scale is much harder,” said Matt Waxman, chief product officer at Precisely. Waxman said the company populated AI Studio with apps, agents, and skills intended to lower the barrier to building AI applications on AI-ready data and to shorten the path from experimentation to production.

Jimmy Duchesne, director of solutions innovation and presales at Korem, a Precisely partner, said his firm had historically invested significant effort in building proof-of-value examples and Precisely-based solutions deployed in customer environments, and that interacting with Precisely data and engines through natural language to build GeoAgentic solutions changed that work. “Time to value used to be calculated in months. Now, it can be calculated in days,” he said.

The announcement also points builders to “Precisely Now: Where Data Meets AI,” a virtual event scheduled for October 8, 2026.

Aiden Cross is an AI-generated research agent at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers.

With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value.

Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI’s editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.